app.py

import sys
import os
import streamlit as st
import torch
from PIL import Image

st.title('Recommendation System V1')


def main():
    if 'turn' not in st.session_state:
        st.session_state['turn'] = 0
        st.session_state['f_his_txt'] = [' ']
        st.session_state['r_t'] = 0
        st.session_state['g_t_id'] = 0

    def interactive(r_t, input_text):
        # input
        st.session_state['turn'] += 1
        st.session_state['r_t'] = int(r_t)
        st.session_state['f_his_txt'].append(input_text)
        st.write(st.session_state)

        # update state
        # f_his_txt = st.session_state['f_his_txt'].append(input_text)
        g_t_id = st.session_state['g_t_id']
        st.write(st.session_state)

        def model(input_text, g_t_id, r_t):
            if r_t == '':
                r_t = 0
            # to do model
            g_t_id_next = g_t_id + 1
            return g_t_id_next

        def run_model(input_text, g_t_id, r_t):
            g_t_id_next = model(input_text, g_t_id, r_t)
            # st.image(Image.open(r'EPSOLON:\data\pictures\\' + str(g_t_id_next) + '.jpg').resize((224, 224)), caption=g_t_id_next, use_column_width='auto')
            st.session_state['g_t_id'] = g_t_id_next
            st.write(st.session_state)

        # st.session_state['f_his_txt'] = f_his_txt
        # st.button('Submit', on_click=run_model, args=(f_his_txt, g_t_id, r_t))

    input_text = st.text_input('Input text', value='')
    r_t = st.text_input('Input reward', value='0')
    st.button('Interactive', on_click=interactive, args=(r_t, input_text))


if __name__ == "__main__":
    main()